直面冲击：人工智能将为数字行业带来怎样的变革

Bracingfor Impact How AI Will TransformDigital Industries What’s inside. The Market, Business Benefits, and Challenges3AI’s Impact in Data Center Networking8AI’s Impact in Telecoms11AI’s Impact on Enterprise Digital Transformation14Spirent’s Top Five Recommendations16Spirent: Your Partner to Unleash the Power of AI19 TheMarket, Business Benefits, and Challenges Artificial intelligence (AI) systems are expected to transformdigital industries in ways still being discovered. In recent years, generative AI (GenAI) has moved from the fringes to the forefront,igniting imaginations about its vast potential. Behind this wave of excitement, industriesare diligently working to prove use cases, scale solutions to meet demand, and innovateto unlock AI’s full potential. Gartner estimates spendingon AI software will grow to$297.9B Despite a seemingly ‘Wild West’ environment, the sheer volume of market participantspursuing AI-based opportunities is fostering a thriving ecosystem, ripe with opportunityand underpinned by rapidly evolving ethics. As corporations race to capitalize on AI,regulators are hastily crafting rules to govern its use. In this eBook, we will cover the complexities of AI’s impact,including challenges and practical strategies for adoption. Stakeholders are abuzz with new opportunities but equally mindful of the growing painsand unforeseen challenges that lie ahead. Businesses don’t just want to join the pack,they want to ensure they are not left behind as markets are disrupted. The starting pointcan seem elusive. In this eBook, we will cover the complexities of AI’s impact, including challenges andpractical strategies for adoption. We’ll also explore the role GenAI will have on keymarket sectors, including data centers, telecom, and banking and financial services. Read on to better understand AI’s potential impact on data center networking, andtelecoms and enterprise digital transformation efforts, and gain actionable insights thatcan help better align your business with the AI revolution. BRAC IN G FO R IM PAC T While traditional AI/ML excels in analyzing network usage andperformance data for predictive planning, GenAI can leverage thisanalysis to generate novel outputs. Together, these technologies makepossible the ongoing, explosive advancement of AI applications we arecurrently seeing. How generative AI compares to traditional AIand machine learning Before we go further, it is important to establish a foundationalunderstanding of the differences between traditional AI and machinelearning (ML), and newer generative AI (GenAI) technology. TraditionalAI and ML have laid the groundwork for predictive analytics anddecision-making processes as a result of being able to analyze andlearn from data. Meanwhile, Generative AI has recently gone a stepfurther with an ability to create new, original content. The following diagram defines AI, ML, and GenAI and explains theevolving landscape of artificial intelligence as GenAI extends thecapabilities of traditional AI/ML. ARTIFICIAL INTELLIGENCE MACHINE LEARNING Artificial Intelligence (AI)encompasses a broad set oftechnologies that enable amachine or system to sense,reason, or act like a human. Machine Learning (ML)is a subsetof AI that enables machines toautonomously extract knowledgefrom data. GENERATIVE AI Generative AI (GenAI)is a newtype of ML that goes beyondpredictive tasks to produce noveland creative outputs such as text,video, and images. IncludesMachine Learning (ML),Computer Vision (CV), RoboticAutomationand more. Traditional AI/MLidentifies datapatterns to perform tasks such aspredictive analysis, object/eventdetection, and speech recognition. GenAIis still in infancy, oftenconfidently presenting inaccurateinformation due to limiteddatasets, training data biases,and imperfect algorithms. Traditional AI/MLsuffers froma lack of generalization andlimited adaptability for dynamicenvironments. BRAC IN G FO R IM PAC T AI’s impact on business cases AI introduces the potential to achieve substantial operational efficiencies and new business outcomes.According to the U.S. Chamber of Commerce, 23% of small businesses already use artificial intelligence formarketing and customer communications. As focus turns to more substantive and consequential roles instrategic business operations, early adopters are targeting outcomes that span: INCREASED REDUCED INCREASED REDUCED REVENUE OPEX CUSTOMEREXPERIENCE By enhancing operationalefficiency and optimizingresource utilization, AI allowsfor more strategic andneed-based managementof equipment upgradesand energy costs, thusminimizing ongoing capitalexpenditures. AI streamlines operationsand cuts costs by proactivelyidentifying and addressinginefficiencies, faults, andareas for improvement inreal time, leading to moreefficient resource utilizationand reduced downtime. AI leverages customerengagement andbehavioral trends touncover new revenueopportunities, enhancingexisting services an